Data from Electronic Health Records Power Research in Rheumatoid Arthritis

Elizabeth Karlson, MD

A patient’s electronic health record (EHR) contains critical information that can help guide an individual’s care. When combined with data from tens of thousands of other patients’ medical records, an EHR can help lead to new insights that could improve the treatment of patients today and in the future. Researchers at BWH have been studying data from EHRs for over a decade to answer questions about a variety of diseases. And with the newly created Partners Biobank Portal, which will harness even more information and measurements transforming Partners eCare data to research data, additional avenues of investigation will soon be possible.

Elizabeth Karlson, MD, who leads the Rheumatic Disease Epidemiology Group in the Section of Clinical Sciences in the Division of Rheumatology, Immunology and Allergy, has been using EHR data to answer pressing questions about rheumatoid arthritis (RA). Up until this year, Karlson and her colleagues used data extracted from BWH’s homegrown EHR system, which relied on programming created at BWH and MGH. The extracted clinical data were transformed to a research format in the Research Patient Data Registry (RPDR). Now, data from Partners eCare can also flow into this repository, creating a more robust resource.

“We’re really looking forward to all of the additional types of data collected in Partners eCare that we’ll be able to start using for research purposes,” said Karlson.

Partners eCare will use Epic’s improved structured data-capture, reporting tools, definitions and dictionaries. It will also allow measurement scales developed by clinical sub-specialists and information collected by using those scales to be included in the repository. All of the data currently in the RPDR will be preserved, even as new functionality is added.

Using Partners eCare, clinicians will continue to record the same measurements that have been collected under the older systems, including information that allows researchers to look at the relationship between medications, diagnoses, laboratory test results, reported side effects and patient outcomes. Some data are easy to extract, but other vital pieces of information may be contained in the sentences and paragraphs written in doctors’ notes. In order to access those points of data, research teams have worked with computer linguistics experts to develop natural language processing (NLP) algorithms, which can extract concepts from text.

“If a patient comes in with RA and her symptoms are flaring, their doctor might write, ‘Joints are painful and swollen, she is having difficulty lifting grocery bags, difficulty turning her house key in the lock.’ Those sorts of sentences can’t be analyzed in a research project, but the underlying concept – that the patient’s disease activity is high – can be,” said Karlson. “Using our NLP system, we would be able to extract that concept.”

Karlson’s team has used this approach to study patients who are non-responders: individuals who are taking medication, but whose symptoms are not getting better. By combining EHR data with genomic information from blood samples, the team hopes to be able to find genetic factors and biomarkers that can predict who will respond well to a particular treatment, allowing for a more tailored, personalized treatment approach in the future.

Karlson and her colleagues are also investigating outcomes for patients with RA. They know that people with RA are twice as likely to have a heart attack; have higher rates of heart disease; and yet, have lower-than-expected cholesterol levels. The team is looking at different subtypes of cholesterol to explore why patients have these paradoxical lipid levels, and are using NLP to screen for the most interesting individuals – those who have heart disease but very low cholesterol levels. The team may follow up to ask those individuals to contribute blood samples, or may use blood samples already in the Partners Biobank for further study. The Partners Biobank, a repository of samples from than 35,000 consented patients, is linked to electronic records, connecting clinical, genomic, imaging and public health data.

“Some people call this ‘big data,’” said Karlson. “Having the electronic tools at researchers’ fingertips to query specific patient populations and define diseases and study outcomes is really tremendous.”

Beyond RA, researchers from across BWH will be able to use the data from Partners eCare to study almost any disease, including heart disease, type 2 diabetes, multiple sclerosis, psychiatric disorders and more. Investigators will also be able to use Partners eCare to recruit patients and develop more nuanced clinical trials that will allow them to more effectively test new drugs and therapies.